User input outside the network training loop This category utilizes the user input to fine-tune the network to over-fit the appearance cues of target object(s) during inference. The representatives are OSVOS [1]} and its following works [2]}, [3]}, [4]}. Since online fine-tuning is required during inference, the drawback of these algorithms is time-consuming, which usually take seconds per image, thus is not practical for the real-world applications.
